320 citations · 760 across the 27 of their papers we have counts for
29 papers
Jagged AI in Scientific Peer Review: Evidence from POMP Data Analysis
Jin Wook Lee, William Szegda, Zhisheng Song +1
Despite their growing use in academic writing and statistical analysis, the performance of artificial intelligence (AI) tools in scientific peer review remains a largely unexplored…
Iterating marginalized Bayes maps for likelihood maximization with application to nonlinear panel models
Jesse Wheeler, Aaron J. Abkemeier, Edward L. Ionides
Complex dynamic systems can be investigated by fitting mechanistic stochastic dynamic models to time series data. In this context, commonly used Monte Carlo inference procedures fo…
Poisson Approximate Likelihood versus the block particle filter for a spatiotemporal measles model
Kunyang He, Yize Hao, Edward L. Ionides
Filtering algorithms for high-dimensional nonlinear non-Gaussian partially observed stochastic processes provide access to the likelihood function and hence enable likelihood-based…
Mechanistic models for panel data: Analysis of ecological experiments with four interacting species
Bo Yang, Jesse Wheeler, Meghan A. Duffy +2
In an ecological context, panel data arise when time series measurements are made on a collection of ecological processes. Each process may correspond to a spatial location for fie…
panelPomp: Analysis of Panel Data via Partially Observed Markov Processes in R
Carles Bretó, Jesse Wheeler, Aaron A. King +1
Panel data arise when time series measurements are collected from multiple, dynamically independent but structurally related systems. Each system's time series can be modeled as a…
Poisson approximate likelihood compared to the particle filter
Yize Hao, Aaron A. Abkemeier, Edward L. Ionides
Filtering algorithms are fundamental for inference on partially observed stochastic dynamic systems, since they provide access to the likelihood function and hence enable likelihoo…